code: def output_shape(self) -> torch.Size:
      return torch.Size([self.size])
  
imports: from typing import List, Optional, Tuple
  import torch
  import torch.nn
  from ludwig.modules.normalization_modules import GhostBatchNormalization
  from ludwig.utils.entmax import Entmax15, EntmaxBisect, Sparsemax
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 4 for calling the AttentiveTransformer obj's underlying member method code with example usage: obj.output_shape() and returns: torch